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The genetic code constrains yet facilitates Darwinian evolution.

Firnberg E, Ostermeier M - Nucleic Acids Res. (2013)

Bottom Line: An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution.We find that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space.However, the constraints endow the code with two advantages: the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA.

ABSTRACT
An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution. Here, we address the extent to which the structure of the standard genetic code constrains evolution by analyzing adaptive mutations of the antibiotic resistance gene TEM-1 β-lactamase and the fitness distribution of codon substitutions in two influenza hemagglutinin inhibitor genes. We find that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space. However, the constraints endow the code with two advantages: the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations. Our findings support the hypothesis that the standard genetic code was shaped by selective pressure to minimize the deleterious effects of mutation yet facilitate the evolution of proteins through imposing an adaptive mutation bias.

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Feasible trajectories for evolving GKQA (colony 14) from TEM-1 (i.e. AEMG) by accumulation of codon substitutions one at a time. Mutations are shown in black, bold letters. Of the 24 possible trajectories, five end with GKQA and four end with GKMA, an allele with equivalent fitness to GKQA. Cefotaxime resistance was measured by plate assay as in Table 1, and the value reported represents the median of three replicates. Data for all replicates are provided in Supplementary Table S3.
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gkt536-F1: Feasible trajectories for evolving GKQA (colony 14) from TEM-1 (i.e. AEMG) by accumulation of codon substitutions one at a time. Mutations are shown in black, bold letters. Of the 24 possible trajectories, five end with GKQA and four end with GKMA, an allele with equivalent fitness to GKQA. Cefotaxime resistance was measured by plate assay as in Table 1, and the value reported represents the median of three replicates. Data for all replicates are provided in Supplementary Table S3.

Mentions: To address whether there is a mutational pathway to any of the alleles with a Hamming distance >4, we chose GKQA (codons: ggg-aag-cag-gca) as a representative allele and constructed the 14 combinations of these four codon substitutions. We considered each codon substitution (whether a point mutation or a multi-bp substitution) as a single mutational step in order to ask whether GKQA could be reached if the genetic code were arranged differently such that each of the required amino acid substitutions were possible with a point mutation. We tested the cefotaxime resistance of these variants and assessed the feasibility of the 24 possible trajectories from TEM-1 to GKQA. We assumed that the evolution of TEM-1 fits the strong selection/weak mutation model of evolution by which the time to fixation or loss of a mutation is much shorter than the time between mutations. Thus, we required that mutations accumulate one at a time with increasing fitness at each step for a trajectory to be deemed feasible, as in a previous study (16). Nine of the 24 possible trajectories were feasible (Figure 1). Four trajectories ended at an intermediate (GKMA) with equivalent resistance to GKQA. Like the feasible trajectories for evolving GKTS (16), the first mutation necessarily occurs at positions 104 or 238, and the fittest double mutant has mutations at both positions (the difference is that 238 is mutated to A instead of S for GKQA). A lack of a mutational trajectory cannot explain why GKQA has not been found in the natural or in vitro evolution of TEM-1. Instead, we posit that the requirement for multiple mutations in a single codon is one reason that makes this allele’s occurrence unlikely. Thus, the architecture of the genetic code constrains evolution by making some viable mutational trajectories improbable.Figure 1.


The genetic code constrains yet facilitates Darwinian evolution.

Firnberg E, Ostermeier M - Nucleic Acids Res. (2013)

Feasible trajectories for evolving GKQA (colony 14) from TEM-1 (i.e. AEMG) by accumulation of codon substitutions one at a time. Mutations are shown in black, bold letters. Of the 24 possible trajectories, five end with GKQA and four end with GKMA, an allele with equivalent fitness to GKQA. Cefotaxime resistance was measured by plate assay as in Table 1, and the value reported represents the median of three replicates. Data for all replicates are provided in Supplementary Table S3.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3753648&req=5

gkt536-F1: Feasible trajectories for evolving GKQA (colony 14) from TEM-1 (i.e. AEMG) by accumulation of codon substitutions one at a time. Mutations are shown in black, bold letters. Of the 24 possible trajectories, five end with GKQA and four end with GKMA, an allele with equivalent fitness to GKQA. Cefotaxime resistance was measured by plate assay as in Table 1, and the value reported represents the median of three replicates. Data for all replicates are provided in Supplementary Table S3.
Mentions: To address whether there is a mutational pathway to any of the alleles with a Hamming distance >4, we chose GKQA (codons: ggg-aag-cag-gca) as a representative allele and constructed the 14 combinations of these four codon substitutions. We considered each codon substitution (whether a point mutation or a multi-bp substitution) as a single mutational step in order to ask whether GKQA could be reached if the genetic code were arranged differently such that each of the required amino acid substitutions were possible with a point mutation. We tested the cefotaxime resistance of these variants and assessed the feasibility of the 24 possible trajectories from TEM-1 to GKQA. We assumed that the evolution of TEM-1 fits the strong selection/weak mutation model of evolution by which the time to fixation or loss of a mutation is much shorter than the time between mutations. Thus, we required that mutations accumulate one at a time with increasing fitness at each step for a trajectory to be deemed feasible, as in a previous study (16). Nine of the 24 possible trajectories were feasible (Figure 1). Four trajectories ended at an intermediate (GKMA) with equivalent resistance to GKQA. Like the feasible trajectories for evolving GKTS (16), the first mutation necessarily occurs at positions 104 or 238, and the fittest double mutant has mutations at both positions (the difference is that 238 is mutated to A instead of S for GKQA). A lack of a mutational trajectory cannot explain why GKQA has not been found in the natural or in vitro evolution of TEM-1. Instead, we posit that the requirement for multiple mutations in a single codon is one reason that makes this allele’s occurrence unlikely. Thus, the architecture of the genetic code constrains evolution by making some viable mutational trajectories improbable.Figure 1.

Bottom Line: An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution.We find that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space.However, the constraints endow the code with two advantages: the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA.

ABSTRACT
An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution. Here, we address the extent to which the structure of the standard genetic code constrains evolution by analyzing adaptive mutations of the antibiotic resistance gene TEM-1 β-lactamase and the fitness distribution of codon substitutions in two influenza hemagglutinin inhibitor genes. We find that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space. However, the constraints endow the code with two advantages: the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations. Our findings support the hypothesis that the standard genetic code was shaped by selective pressure to minimize the deleterious effects of mutation yet facilitate the evolution of proteins through imposing an adaptive mutation bias.

Show MeSH
Related in: MedlinePlus